1 00:00:00,140 --> 00:00:03,240 Thank you for tuning into the Becker's Healthcare Podcast. I am Molly Gamble, 2 00:00:03,350 --> 00:00:06,800 vice President Editorial, and today I'm catching up with Dr. William Maurice. 3 00:00:07,380 --> 00:00:10,120 Dr. Maurice is president of the Mayo Clinic Laboratories. 4 00:00:10,300 --> 00:00:12,640 He has been with the Mayo System for 23 years, 5 00:00:13,030 --> 00:00:16,720 including roles as Professor of laboratory Medicine and pathology with Mayo 6 00:00:16,720 --> 00:00:20,400 Clinic School of Medicine and Division Chair of Laboratory Medicine and 7 00:00:20,400 --> 00:00:23,840 Pathology. Dr. Maurice, thank you so much for joining me today. 8 00:00:24,060 --> 00:00:25,760 How are you and where do we find you? 9 00:00:26,820 --> 00:00:29,720 Um, uh, thank you for having me on number one. I, it's, 10 00:00:29,720 --> 00:00:32,880 it's a great pleasure to join you. Uh, I'm doing well. Uh, 11 00:00:32,880 --> 00:00:37,220 I've actually been at Mayo for, for longer than I've been here since 87. 12 00:00:37,250 --> 00:00:40,100 I've lost counted the actual years cause I came here for medical school and 13 00:00:40,260 --> 00:00:43,860 graduate school and, and never left. So I've been here for a long time. 14 00:00:44,160 --> 00:00:46,580 And that's where you find me today is in Rochester, Minnesota. 15 00:00:47,150 --> 00:00:51,100 Great. Well you took an opportunity that could have made you younger and, 16 00:00:51,160 --> 00:00:54,460 and you correct me, which I appreciate. I had my facts wrong there, Dr. Marie. 17 00:00:54,560 --> 00:00:58,900 So you've been there 87. That's says old as I am actually. So . Um, 18 00:00:58,900 --> 00:01:00,540 really, really impressive longevity. 19 00:01:01,990 --> 00:01:04,800 Yeah, it's the cold weather. It keeps you cryopreserved, so that's good. 20 00:01:05,920 --> 00:01:08,250 Well, let's talk a little bit about the lab. You know, 21 00:01:08,250 --> 00:01:09,290 I thought we could start there. 22 00:01:09,430 --> 00:01:14,050 The lab has always been so important to diagnostics and care delivery, 23 00:01:14,270 --> 00:01:19,090 but it seems like Covid 19 really threw labs into the center stage as 24 00:01:19,290 --> 00:01:23,570 everyone and their brother just gained at least a bit more familiarity with 25 00:01:23,600 --> 00:01:25,650 diagnostics and lab testing. My, you know, 26 00:01:25,650 --> 00:01:29,970 hearing my 95 year old grandmother talk about p c r tests, for instance. Um, 27 00:01:30,310 --> 00:01:35,130 how did renewed reliance on labs throughout the pandemic come home to 28 00:01:35,130 --> 00:01:35,963 affect your work? 29 00:01:37,480 --> 00:01:41,490 Well, um, I think that the, the visibility, obviously, 30 00:01:41,550 --> 00:01:44,930 as you mentioned right away, uh, it's a part of healthcare. Uh, 31 00:01:44,930 --> 00:01:48,370 even most people that choose laboratory medicine pathology as a medical career 32 00:01:48,500 --> 00:01:52,330 often do so after they've done other areas of practice. For myself, 33 00:01:52,370 --> 00:01:56,330 I did internal medicine first, um, just because it's not, so even within the, 34 00:01:56,350 --> 00:01:59,930 within the practice of medicine, it's not so obvious of the career choice. 35 00:02:00,070 --> 00:02:04,090 So that immediate visibility, um, was really quite, uh, 36 00:02:04,290 --> 00:02:06,810 profound and also need for understanding, right, uh, 37 00:02:06,830 --> 00:02:10,850 for people to really understand what is the role. Because now you have a test. 38 00:02:10,930 --> 00:02:15,890 First of all, where did the test come from? What's, what is the, um, 39 00:02:15,950 --> 00:02:19,010 you know, what is the entire life cycle of a test and meaning, 40 00:02:19,010 --> 00:02:20,330 what does it take to bring a test up? 41 00:02:20,330 --> 00:02:24,850 Because I remember early days March of 2020, uh, I was in Washington, 42 00:02:24,910 --> 00:02:28,290 DC as part of the American Clinical Laboratory Association's board meeting. 43 00:02:28,390 --> 00:02:31,610 I'm now the, actually the chair of that board. Um, 44 00:02:31,830 --> 00:02:34,130 and we were called to the Pence White House to, 45 00:02:34,130 --> 00:02:36,410 to meet with the Pence team on testing. And they, you know, 46 00:02:36,410 --> 00:02:39,010 that was the day that Trump made the announcement that every American that 47 00:02:39,010 --> 00:02:43,290 wanted to test or needed a test was gonna get a test and the test didn't exist. 48 00:02:43,510 --> 00:02:44,570 So I think it just, 49 00:02:44,790 --> 00:02:48,290 the whole idea of what does it take to build a test infrastructure? 50 00:02:48,960 --> 00:02:52,250 What does a test mean for an individual? What kind of information do you need? 51 00:02:52,250 --> 00:02:54,530 Because it's not just a test, but what does it mean for you? 52 00:02:54,830 --> 00:02:58,650 All that stuff was really thrust into the, into the, into the limelight for a, 53 00:02:58,750 --> 00:03:01,940 for a prolonged period of time. I mean, it was well over 12, 54 00:03:01,940 --> 00:03:04,620 16 months that we're really talking about testing once some way, 55 00:03:04,620 --> 00:03:07,860 shape or form as a major, a major news story globally. 56 00:03:09,120 --> 00:03:12,580 Do, do you think it did anything for expectations? You know, I remember too, 57 00:03:12,640 --> 00:03:14,860 you were talking about the early days of the pandemic and I, 58 00:03:14,940 --> 00:03:18,540 I think there was some frustration depending on where you were in this varied 59 00:03:18,690 --> 00:03:22,420 city to city, but wait times for test results. Uh, 60 00:03:22,440 --> 00:03:25,420 do you think by better understanding the entire, you know, 61 00:03:25,420 --> 00:03:29,020 test creation in individual testing like you mentioned, 62 00:03:29,400 --> 00:03:33,540 do you think the public gained more information and understanding of 63 00:03:34,550 --> 00:03:36,260 turnaround times or, 64 00:03:36,440 --> 00:03:41,220 or do people continue to have like Uber eats DoorDash expectations for 65 00:03:41,220 --> 00:03:43,900 immediate results like they do in most things right now? 66 00:03:44,530 --> 00:03:46,780 Well, I certainly, I think that, um, 67 00:03:47,360 --> 00:03:51,100 it created consternation for all of us that needed a test that they were so 68 00:03:51,100 --> 00:03:53,860 inaccessible. And I, and I, I think it really, 69 00:03:53,880 --> 00:03:56,660 it raised people's expectations about, um, 70 00:03:56,660 --> 00:04:00,140 cuz we've been able to do home testing for a long time. It's been a relatively, 71 00:04:00,300 --> 00:04:03,060 a very minor part of the overall testing, uh, 72 00:04:03,380 --> 00:04:05,020 landscaping the United States and globally. 73 00:04:05,490 --> 00:04:07,900 There's a real now and much more of an interest in this. 74 00:04:07,930 --> 00:04:11,420 It's probably not at the height of where it was say in now omicron wave of 75 00:04:11,420 --> 00:04:11,880 covid, 76 00:04:11,880 --> 00:04:15,460 but still there's I think a societal expectation that there's gonna be more 77 00:04:15,460 --> 00:04:18,180 accessibility to testing. Um, and, 78 00:04:19,360 --> 00:04:23,420 and also there's been a massive investment in the infrastructure cuz a lot of it 79 00:04:23,420 --> 00:04:27,220 was just that the inf the reimbursement of labs is such that it didn't really 80 00:04:27,220 --> 00:04:31,020 drive a lot of, uh, excess in the supply chain on tests. 81 00:04:31,360 --> 00:04:34,500 So now there's been a massive global investment in testing infrastructure. 82 00:04:34,760 --> 00:04:38,700 That's part of the dialogue we have to have in healthcare going forward is what 83 00:04:38,700 --> 00:04:40,340 are societal expectations around testing? 84 00:04:40,920 --> 00:04:44,740 How do we use what we've invested in to get us ramped up to provide testing for, 85 00:04:44,800 --> 00:04:48,820 for individuals and for patients, and how do we carry that forward? Uh, 86 00:04:48,860 --> 00:04:51,300 I think that's really important and it, and it, 87 00:04:51,460 --> 00:04:53,900 it is a societal question because, uh, 88 00:04:53,920 --> 00:04:57,020 as much as we think about convenience and the inconvenience of having to wait 89 00:04:57,020 --> 00:04:57,760 for a test, 90 00:04:57,760 --> 00:05:01,620 we also know that outcomes in covid were directly could be directly linked to 91 00:05:01,620 --> 00:05:04,460 access to testing, right? So, so areas and, and, 92 00:05:04,480 --> 00:05:07,780 and populations that lower access to testing tend to have poor outcomes. 93 00:05:08,000 --> 00:05:12,500 So we now really see this as part of the whole landscape of disparities as well 94 00:05:12,500 --> 00:05:13,820 as access and convenience. 95 00:05:16,040 --> 00:05:18,940 Dr. Maurice, let's talk a bit more about Mayo Clinic. You know, 96 00:05:18,940 --> 00:05:20,940 you mentioned you've been there for about 35 years, 97 00:05:21,640 --> 00:05:24,980 an exceptional place for healthcare, both on a national level, 98 00:05:24,980 --> 00:05:25,940 international level. 99 00:05:26,480 --> 00:05:31,060 Can you share some points of pride with me about Mayo's clinical or lab 100 00:05:31,060 --> 00:05:32,020 capabilities? I, 101 00:05:32,120 --> 00:05:36,420 I'm really talking to someone who heads up a lab at the best of the best in what 102 00:05:36,700 --> 00:05:39,300 American healthcare can be and can do. I'm, 103 00:05:39,360 --> 00:05:43,140 I'm curious if you have any stories that can encapsulate the possibility of what 104 00:05:43,140 --> 00:05:44,460 can be achieved at Mayo Clinic. 105 00:05:45,650 --> 00:05:50,620 Yeah, I'd love to. Obviously I've devoted my whole career to the place and, um, 106 00:05:50,800 --> 00:05:54,780 and I've obviously, and Mayo has done so much to enrich my own personal life, 107 00:05:54,780 --> 00:05:56,940 professionally and done so, I think does so much for, 108 00:05:57,720 --> 00:06:00,140 for healthcare in this country and globally. Uh, 109 00:06:00,140 --> 00:06:04,490 and I think it's important that institutions like Mayo Clinic really continue 110 00:06:04,710 --> 00:06:06,090 to, to, to be a, 111 00:06:06,170 --> 00:06:10,490 a voice in healthcare where healthcare is going specifically for diagnostics is 112 00:06:10,490 --> 00:06:15,210 very interesting in that. Um, so we have 150 plus year history, right, uh, of, 113 00:06:15,310 --> 00:06:17,290 of, of our institution, uh, 114 00:06:17,290 --> 00:06:21,210 very unique founding here in in rural Minnesota and then spreading from there. 115 00:06:21,510 --> 00:06:22,530 But if you look back, 116 00:06:23,440 --> 00:06:27,450 diagnostics a and laboratory medicine were actually one of the, the earliest, 117 00:06:28,310 --> 00:06:30,090 um, investments by the Mayo Brothers. 118 00:06:30,090 --> 00:06:31,690 We think of the Mayo Brothers and surgeons, 119 00:06:31,910 --> 00:06:36,250 but a lot of the very early innovations in diagnostics actually came out of Mayo 120 00:06:36,250 --> 00:06:39,730 Clinic, whether it's intraoperative frozen section, which was, you know, 121 00:06:39,730 --> 00:06:43,530 at the turn of the century or the first grading of tumors, uh, by Dr. 122 00:06:43,600 --> 00:06:47,970 Broders in the 1920s. It just goes on and on. And so the question is, you know, 123 00:06:48,110 --> 00:06:50,170 why, you know, why is that so important? 124 00:06:50,310 --> 00:06:53,330 Why was that so important to the Mayo Brothers and to the, 125 00:06:53,330 --> 00:06:55,770 to the early founders of Mayo Clinic? Um, 126 00:06:55,790 --> 00:06:59,890 and it really goes back to our model of care is is and what I'm really proud of, 127 00:06:59,890 --> 00:07:02,770 what's kept me here are values our Franciscan values, 128 00:07:02,870 --> 00:07:04,650 but teamwork is one of those key ones. 129 00:07:04,670 --> 00:07:08,850 And so the whole Mayo Vision was that you would have physicians and providers, 130 00:07:08,900 --> 00:07:12,930 healthcare professionals that focused on the need of the patient that when a 131 00:07:12,930 --> 00:07:14,530 patient came through the front door Mayo Clinic, 132 00:07:14,530 --> 00:07:16,290 they had a team of people that were all their, 133 00:07:16,290 --> 00:07:18,530 their primary job was working together, right? 134 00:07:18,550 --> 00:07:22,330 To understand and what came to be very serious and complex illnesses that 135 00:07:22,330 --> 00:07:24,170 couldn't get answered elsewhere, people were coming here. 136 00:07:24,960 --> 00:07:27,170 Information for that is actually the data. 137 00:07:27,590 --> 00:07:32,450 Any team functions best when there's clear understanding of the context i e the 138 00:07:32,450 --> 00:07:35,410 data, right? And, and good communication of that. So I think this, 139 00:07:35,560 --> 00:07:39,290 this whole investment of labs is really seeing labs cuz labs generate 70, 140 00:07:39,290 --> 00:07:41,850 80% of the quantitative data in the medical record, right? 141 00:07:42,070 --> 00:07:46,890 So the idea that diagnostics were so key for a team-based practice 142 00:07:46,950 --> 00:07:49,610 of medicine and the first integrated medical practice to work, 143 00:07:49,910 --> 00:07:53,890 that's the pride that I take in working at Mayo. And I, I tell people, 144 00:07:53,930 --> 00:07:56,610 I don't know if I would've done pathology but would've been at Mayo Clinic 145 00:07:56,760 --> 00:08:00,610 because we are as pathologists and laboratory in such an integral part of the 146 00:08:00,610 --> 00:08:01,850 care teams, um, 147 00:08:02,000 --> 00:08:06,090 what makes me really proud is the fifth year history of Mayo Clinic Labs because 148 00:08:06,160 --> 00:08:08,490 that through that activity of the reference lab, 149 00:08:08,940 --> 00:08:12,690 we've been able to open that team-based model of care outside of our campuses, 150 00:08:12,780 --> 00:08:13,130 right? 151 00:08:13,130 --> 00:08:17,610 Because patients can interact with the data and the providers and we can inform 152 00:08:17,610 --> 00:08:20,290 the care of that patient without them being around our campus through Mayo 153 00:08:20,290 --> 00:08:22,450 Clinic Laboratories. And so it, but it all, 154 00:08:22,830 --> 00:08:27,450 it forms a very much a symbiotic relationship where interacting with patients on 155 00:08:27,450 --> 00:08:31,210 the outside brings information into our institution that we can then learn from 156 00:08:31,210 --> 00:08:33,250 and share more information. Um, 157 00:08:33,390 --> 00:08:37,970 and so one real tangible example of that is we've had a long history of 158 00:08:37,970 --> 00:08:40,670 neurologic, very strong neurology practice. 159 00:08:41,170 --> 00:08:45,680 We see patients that come in many times after they've had other cancers or 160 00:08:45,790 --> 00:08:49,480 neoplasms and they have disorders of their neurologic system that are very 161 00:08:49,480 --> 00:08:51,040 difficult to understand and diagnose. 162 00:08:51,430 --> 00:08:56,420 Well it turns out that your brain and your central nervous system expresses over 163 00:08:56,420 --> 00:09:00,100 80% of the proteins in your body. So when you have something like a cancer, 164 00:09:00,440 --> 00:09:03,740 you can start to get antibodies to those proteins or immune reaction to the 165 00:09:03,740 --> 00:09:07,940 proteins or autoimmunity that can cause very specific and treatable, 166 00:09:08,240 --> 00:09:10,980 but sometimes irreversible if not treated neurologic diseases. 167 00:09:11,200 --> 00:09:16,140 And we now have a laboratory in Rochester that is staffed by 168 00:09:16,140 --> 00:09:19,820 neurologist who are seeing these patients and identifying these new, 169 00:09:20,280 --> 00:09:22,860 cuz there's so many, there's these new patterns of disease, 170 00:09:23,200 --> 00:09:26,940 but then we can make available to the outside world. So, so it's really that, 171 00:09:26,940 --> 00:09:30,820 that kind of ability to make the, the Mayo Clinic model more inclusive. 172 00:09:30,970 --> 00:09:34,260 That that, that's part of my real pride in working at Mayo Clinic, 173 00:09:34,320 --> 00:09:35,940 in lab medicine at Mayo Clinic Labs. 174 00:09:37,520 --> 00:09:40,580 And even the story of the origins of lab at Mayo Clinic. You know, 175 00:09:40,580 --> 00:09:43,700 you mentioned the Mayo Brothers are known predominantly for being surgeons, 176 00:09:43,700 --> 00:09:46,780 but also one of their fo first focus areas was the lab. 177 00:09:46,780 --> 00:09:50,060 That kind of goes back to your earlier remarks about how pathology sometimes 178 00:09:51,000 --> 00:09:52,300 blends into the background. 179 00:09:52,300 --> 00:09:54,460 It doesn't always receive the recognition that it should. 180 00:09:55,530 --> 00:09:58,260 Yeah. And it's just because we interact with it and I think that's coming, 181 00:09:58,260 --> 00:10:01,660 it goes back to the pandemic. Cuz most of the time when we think about the lab, 182 00:10:01,660 --> 00:10:05,380 we think about going to the doctor, doctor orders a test, test comes back. 183 00:10:05,520 --> 00:10:09,260 The interaction is very much with that, with that provider haven't been there. 184 00:10:09,260 --> 00:10:10,820 But then you start to step back. 185 00:10:11,110 --> 00:10:13,380 Covid forced us to take the macro view of testing. 186 00:10:13,810 --> 00:10:16,780 What does testing do for healthcare? What does testing do for society? 187 00:10:16,840 --> 00:10:19,020 How should testing be used going forward? 188 00:10:19,560 --> 00:10:22,820 And also the focus on the need for innovation, right? Because everything, 189 00:10:22,820 --> 00:10:26,380 whether it's covid and a new pathogen or what I just described, 190 00:10:26,770 --> 00:10:30,180 it's also a real hotbed for innovation. So we have to really think about that. 191 00:10:31,000 --> 00:10:33,660 Um, and last but not least in the, 192 00:10:33,760 --> 00:10:37,660 we are in the era of now big data and we just think now about large language 193 00:10:37,660 --> 00:10:38,660 models and everything else. 194 00:10:39,160 --> 00:10:42,500 If you think to the fact that 70 to 80% of data coming into the health rate 195 00:10:42,500 --> 00:10:46,780 comes out of the laboratories, even from a healthcare perspective, uh, 196 00:10:46,780 --> 00:10:47,740 and healthcare delivery, 197 00:10:47,740 --> 00:10:50,140 you still have to start thinking about that in a much different way. 198 00:10:50,480 --> 00:10:51,620 Mm-hmm. . Mm-hmm. , 199 00:10:52,490 --> 00:10:56,730 I wanted to get a sense from you about how much of a concern over utilization 200 00:10:56,830 --> 00:10:59,130 of, of diagnostics or lab testing is. 201 00:10:59,870 --> 00:11:03,610 And I it seems as though there's so much, so, 202 00:11:03,750 --> 00:11:07,810 so much in healthcare is scarce right now or in short supply and it's been that 203 00:11:07,810 --> 00:11:09,410 way actually for, you know, for a number of years. 204 00:11:10,150 --> 00:11:11,730 But the issue of over the utilization, 205 00:11:11,790 --> 00:11:15,610 it doesn't seem like it gets the attention or the amount of conversation that it 206 00:11:15,610 --> 00:11:19,010 once did. Dr. Maurice, I'm curious, what's your view on this? 207 00:11:19,150 --> 00:11:23,290 How pressing of a problem is it, have we come, have we made any progress in, 208 00:11:23,430 --> 00:11:26,690 in accounting for it through data like you may mention of, 209 00:11:26,710 --> 00:11:29,490 or is it still something that is persistent? 210 00:11:31,070 --> 00:11:35,810 Um, I think it's still a hill that we have yet to climb. And I think it's a, 211 00:11:35,810 --> 00:11:39,410 it is a problem for, for my profession, for laboratory medicine. 212 00:11:39,410 --> 00:11:43,130 It's a problem for healthcare. But if you think about laboratories, um, 213 00:11:43,210 --> 00:11:44,330 that over utilization, 214 00:11:44,530 --> 00:11:49,210 I think that some of the studies have suggested that 30% or more of tests are 215 00:11:49,210 --> 00:11:52,970 overutilized you know, 30%, there's 30% excess in testing that's performed. 216 00:11:54,000 --> 00:11:57,140 It really does a few things that are really bad for patients and bad for 217 00:11:57,140 --> 00:12:00,340 healthcare. First of all, there's just the waste of the, of the testing itself. 218 00:12:01,160 --> 00:12:03,580 Second of all, it really forces, it, 219 00:12:03,640 --> 00:12:07,300 it drives you to think about something more as a commodity as opposed to an 220 00:12:07,350 --> 00:12:10,740 asset, right? So if we're over utilizing tests, we think oh, 221 00:12:10,740 --> 00:12:13,020 we can just do so many tests. We're now, 222 00:12:13,020 --> 00:12:16,260 that's one of the things that precludes us from seeing the value in testing for 223 00:12:16,260 --> 00:12:18,340 healthcare and for individuals. Um, 224 00:12:18,360 --> 00:12:23,140 and then last but not least is that that data actually drives 225 00:12:23,530 --> 00:12:28,100 more over utilization. So my passion and my, my background is, 226 00:12:28,100 --> 00:12:32,380 and expertise is in the diagnosis of blood cancers and particularly difficult to 227 00:12:32,580 --> 00:12:35,180 diagnose blood cancers, uh, a certain part of the immune system. 228 00:12:35,760 --> 00:12:39,740 And most of the time I would see patients getting evaluated for these diseases. 229 00:12:40,510 --> 00:12:43,780 Often it's because there've been overutilization of other tests that made the 230 00:12:43,780 --> 00:12:46,460 doctor think, oh no, I gotta rule out this rare cancer, right? 231 00:12:46,520 --> 00:12:50,340 As opposed to if we'd been more intentional about how we use the entirety of the 232 00:12:50,340 --> 00:12:51,173 laboratory, 233 00:12:51,200 --> 00:12:55,540 we can really focus those high power tools on the patients that really need it. 234 00:12:56,050 --> 00:12:58,620 What we're seeing is if we don't do that now, 235 00:12:58,620 --> 00:13:02,180 there's pushback from payers to actually pay for the test. So on the one hand, 236 00:13:02,590 --> 00:13:04,860 especially going into Covid now coming out, 237 00:13:05,660 --> 00:13:08,880 the promise was on individualized medicine or personalized medicine, 238 00:13:09,130 --> 00:13:13,360 which really connotes a deep level of diagnostics around each person so you 239 00:13:13,360 --> 00:13:16,560 really understand their disease. Those tend to be more expensive tests. 240 00:13:17,220 --> 00:13:20,240 If there's not a strong rationale to a payer for why they're being performed, 241 00:13:20,390 --> 00:13:23,840 they just see a more expensive test that's probably driving a more expensive 242 00:13:23,840 --> 00:13:24,673 therapeutic. 243 00:13:24,740 --> 00:13:28,880 So what it does ultimately is it actually decreases access to the more 244 00:13:28,880 --> 00:13:33,320 specialized care cuz over utilization is forcing payers to think of things more 245 00:13:33,320 --> 00:13:36,840 in bulk and just trying to drive out cost as opposed to creating value with the 246 00:13:36,840 --> 00:13:37,673 laboratories. 247 00:13:39,610 --> 00:13:41,780 That makes sense. Can you, just to make sure I understand you clear, 248 00:13:41,780 --> 00:13:45,700 can you walk me through an example of the lab data, 249 00:13:45,880 --> 00:13:48,140 the testing data actually driving more utilization? 250 00:13:48,260 --> 00:13:51,060 I think you just did at a high level on how payers receive it, 251 00:13:51,320 --> 00:13:52,980 but can you almost walk me through if, 252 00:13:52,980 --> 00:13:56,700 if there were a specific case you could illustrate for me so I better understand 253 00:13:56,700 --> 00:13:57,580 that, that thought? 254 00:13:57,810 --> 00:14:02,580 Sure, sure. So a, a really good example would be in cancer care again, right? 255 00:14:03,120 --> 00:14:07,540 And if you think now we are starting to migrate or, 256 00:14:07,560 --> 00:14:12,500 or really progress our thinking in medicine to think of can most 257 00:14:12,500 --> 00:14:15,460 organs we think of as organ-based cancers, right? There's lung cancer, 258 00:14:15,460 --> 00:14:17,260 there's colon cancer, there's breast cancer. 259 00:14:17,680 --> 00:14:20,540 To where now we're really understanding these as pathway diseases. 260 00:14:20,540 --> 00:14:21,540 Meaning there's certain, 261 00:14:21,540 --> 00:14:26,180 there's certain pathways by which cells grow and differentiate and know when to 262 00:14:26,180 --> 00:14:29,780 stop growing that can get perturbed in different sites in the body. 263 00:14:29,800 --> 00:14:31,900 And when they do, they can lead to cancer. 264 00:14:32,400 --> 00:14:36,020 And so the drugs are more targeted at those pathways, right? 265 00:14:36,240 --> 00:14:38,220 So we get much more specific treatment. 266 00:14:39,160 --> 00:14:42,420 The way we detect those is with typically with expensive next generation 267 00:14:42,420 --> 00:14:45,500 sequencing tests. And so those tests are much more, 268 00:14:45,500 --> 00:14:48,980 when we think of tests as being a few hundred dollars, that's one thing. 269 00:14:48,980 --> 00:14:52,660 When you think of tests being five, $6,000, it just gets a lot more attention. 270 00:14:53,690 --> 00:14:57,260 What I think payers are seeing is they see, uh, uh, 271 00:14:57,280 --> 00:14:59,700 an an increase in the use of these tests, right? 272 00:14:59,760 --> 00:15:01,900 So they can see now their lab spend is going up, 273 00:15:02,130 --> 00:15:04,780 it's going up on these more esoteric tests. Um, 274 00:15:05,000 --> 00:15:08,340 and at the flip side is they can also see the specialty farmer going up, 275 00:15:08,720 --> 00:15:11,060 but then they try and link them together in their databases. 276 00:15:11,060 --> 00:15:14,100 They don't see any rationale. So they'll see a patient get a, you know, 277 00:15:14,420 --> 00:15:17,940 a very expensive test, maybe get one or two cycles of a drug. 278 00:15:18,090 --> 00:15:19,460 They can't actually match that. 279 00:15:19,460 --> 00:15:22,900 The test results drove the prescription of the drugs. So now they just say, 280 00:15:22,900 --> 00:15:26,660 well let's put in a lot of prior authorization just so it's not too many people 281 00:15:26,720 --> 00:15:31,260 get this test cuz So it's the only tool that they have as opposed to let's work 282 00:15:31,260 --> 00:15:33,060 with academic medical centers, 283 00:15:33,150 --> 00:15:36,780 let's work with medicine to develop treatment guidelines so that we actually 284 00:15:36,780 --> 00:15:40,260 think about the testing as part of that treatment guideline cuz then will then 285 00:15:40,260 --> 00:15:44,020 drive the use of the therapeutics. So that's an example that's seeing thousands, 286 00:15:44,280 --> 00:15:45,340 you know, of of, 287 00:15:45,520 --> 00:15:50,380 of these tests being performed without any kind of care-based rationale for the 288 00:15:50,380 --> 00:15:53,300 performance of the test and then driving expensive drugs. Hope, 289 00:15:53,300 --> 00:15:54,380 hopefully that makes sense. 290 00:15:55,560 --> 00:15:59,300 No, it does. Thank you. Thank you very much for the example. Um, yeah, 291 00:15:59,440 --> 00:16:01,180 I'm curious about that. I think you, you raised some, 292 00:16:01,180 --> 00:16:02,460 some really good stats there. 293 00:16:02,460 --> 00:16:06,860 You know how it's still a hill we have to climb 30% or more of tests are 294 00:16:06,860 --> 00:16:08,420 overutilized also. 295 00:16:08,420 --> 00:16:11,940 I i I think it's a really interesting point you raised about how it can drive 296 00:16:12,000 --> 00:16:16,420 one to think about testing as a commodity more so than an asset. 297 00:16:17,080 --> 00:16:20,980 Is that something that you've seen as a long-term like cultural risk almost and 298 00:16:21,000 --> 00:16:23,180 how diagnostics are, 299 00:16:23,600 --> 00:16:26,020 are treated and thought of in a system? 300 00:16:27,090 --> 00:16:28,270 Yes, it is a, 301 00:16:28,420 --> 00:16:32,440 it's a risk for healthcare for patients and it lies on both ends of the 302 00:16:32,560 --> 00:16:35,920 spectrum. Because on the flip side, there's often, 303 00:16:35,920 --> 00:16:38,840 when we talk about over-utilization and you think about less expensive tests, 304 00:16:39,180 --> 00:16:42,840 we know there's a lot of tests that are actually underutilized and particularly 305 00:16:42,840 --> 00:16:46,840 in the management of chronic illnesses. And that kind of goes back to, um, 306 00:16:46,840 --> 00:16:47,880 when you, the, to me, 307 00:16:48,020 --> 00:16:52,280 if we start to think about diagnostics as a tool that can help us to bend the 308 00:16:52,280 --> 00:16:55,760 cost curve in healthcare, which we have to do as to how do you use he, 309 00:16:55,760 --> 00:16:58,040 how do use diagnostics across that continuum of care. 310 00:16:58,540 --> 00:17:03,120 Cuz we probably are under utilizing at home or easily accessible tests to help 311 00:17:03,120 --> 00:17:06,080 manage chronic diseases to make sure patients don't get into trouble like 312 00:17:06,400 --> 00:17:07,960 diabetes or heart disease, right? 313 00:17:08,100 --> 00:17:10,760 So we might have underutilization at that end of the spectrum and 314 00:17:10,760 --> 00:17:12,200 overutilization at other ends. 315 00:17:12,260 --> 00:17:17,040 So really thinking about what diagnostics can do holistically to drive value in 316 00:17:17,040 --> 00:17:20,360 healthcare across the board from, you know, 317 00:17:20,360 --> 00:17:24,890 intensive episodes of care around cancer to the management of chronic diseases, 318 00:17:24,970 --> 00:17:26,210 I think is where we need to go. 319 00:17:26,830 --> 00:17:29,650 And that's why being smart about how we use the test, 320 00:17:31,290 --> 00:17:34,870 the purpose and the value that they're creating in each episode will be really 321 00:17:34,870 --> 00:17:39,190 important. And, and there again, we had those conversations in Covid. 322 00:17:40,170 --> 00:17:43,070 How can we make them persist when we talked about screening tests and their 323 00:17:43,070 --> 00:17:46,910 value in helping protect people from the spread of disease and those things, 324 00:17:46,910 --> 00:17:49,340 right? You have to think about, it's not just a test, 325 00:17:49,930 --> 00:17:53,100 it's a question you're trying to answer and the setting that it's in, 326 00:17:53,290 --> 00:17:54,620 that we all have to come together. 327 00:17:54,960 --> 00:17:57,020 And so it really is very much a healthcare issue. 328 00:17:57,520 --> 00:18:00,080 Mm-hmm. We've talked a bit about covid, 329 00:18:00,210 --> 00:18:02,400 we've talked about about Mayo and its history. 330 00:18:02,400 --> 00:18:06,120 We've talked about still some challenges that the system needs to confront. 331 00:18:06,690 --> 00:18:11,400 Let's talk about what's new, what's a relatively new or emerging issue. Dr. 332 00:18:11,400 --> 00:18:15,480 Marie said it's been commanding a significant amount of your attention as of 333 00:18:15,480 --> 00:18:16,280 late. Uh, 334 00:18:16,280 --> 00:18:19,680 I would love to learn more about it and also why you find it so compelling or 335 00:18:19,680 --> 00:18:20,880 concerning in this moment. 336 00:18:22,180 --> 00:18:26,080 Um, it really twofold. I'll talk about the, the, 337 00:18:26,180 --> 00:18:29,360 the medical side first and then sort of the, the, the, 338 00:18:30,140 --> 00:18:34,600 the policy side second. Um, so I think on, on the medical side, 339 00:18:34,710 --> 00:18:38,720 it's an extraordinarily exciting time and I think I, I have the benefit of, 340 00:18:38,730 --> 00:18:43,040 again, growing up and being, I I tell people I'm home ized . 341 00:18:43,040 --> 00:18:45,640 I mean I've only been in Mayo, so, but to be, 342 00:18:45,640 --> 00:18:47,280 it's a very boundaryless if you think about it, 343 00:18:47,280 --> 00:18:51,160 it's a whole ethos of our institutions around teamwork and then we tend to be 344 00:18:51,760 --> 00:18:56,120 boundaryless in our areas of care. So I don't think about a machine, 345 00:18:56,240 --> 00:18:59,680 I think about the lab and I think about radiology and I think about the patient 346 00:18:59,940 --> 00:19:04,560 and I we're entering an era where all this data can start to flow together. 347 00:19:04,860 --> 00:19:08,840 Uh, digital pathology is sort of the last, will be one of the last strongholds, 348 00:19:08,840 --> 00:19:12,240 if you will, of the old way of practicing, like practicing laboratory medicine. 349 00:19:12,270 --> 00:19:17,120 Once we get to where the actual histology is digitized and we can see continued 350 00:19:17,120 --> 00:19:20,080 evolution of things like chat, G p t and large language models, 351 00:19:20,420 --> 00:19:24,760 you can start to imagine where having all this information can come together 352 00:19:24,790 --> 00:19:28,000 much more rapidly and seamlessly for a patient. So the, 353 00:19:28,180 --> 00:19:32,360 so the lab rather being as symptomatic of fragmentation and care is actually a 354 00:19:32,600 --> 00:19:34,920 solution. We think about tools that sit on top of diagnostics, 355 00:19:34,920 --> 00:19:38,200 whether they're radiology or labs that actually create a much more seamless 356 00:19:38,200 --> 00:19:41,800 experience for a patient and let them know where they need to go, access care, 357 00:19:41,800 --> 00:19:44,320 what level, et cetera, et cetera. To me that's a, 358 00:19:44,320 --> 00:19:48,080 that's a super exciting time cuz that's what I've always thought about is that 359 00:19:48,080 --> 00:19:48,280 the, 360 00:19:48,280 --> 00:19:51,840 the whole purpose of this is to get as much information around that patient and 361 00:19:51,840 --> 00:19:54,440 the provider, the physician to really create meaning for them. 362 00:19:54,740 --> 00:19:57,400 And so this is a time we could actually achieve that in, 363 00:19:57,400 --> 00:20:00,000 in ways that we never could before. Um, 364 00:20:00,620 --> 00:20:03,440 so that's my passion is driving towards that and again, 365 00:20:03,440 --> 00:20:07,040 thinking about everything from at-home testing to the really esoteric stuff that 366 00:20:07,040 --> 00:20:08,920 we do at Mayo Clinic. In that equation, 367 00:20:10,060 --> 00:20:14,560 the concern that I have really is around, uh, around policy. Uh, particularly, 368 00:20:14,660 --> 00:20:18,440 uh, you know, in my role at the American Clinical Laboratory Association, 369 00:20:18,940 --> 00:20:22,160 we still have the protecting access to Medicare Act, which is, you know, 370 00:20:22,160 --> 00:20:25,600 if there's not another delay, we'll see a drop in reimbursement. Uh, 371 00:20:25,620 --> 00:20:28,400 for many of the, of the, of the more commonly ordered tests, 372 00:20:28,950 --> 00:20:30,640 labs are already financially strapped. 373 00:20:30,960 --> 00:20:34,160 Laboratories are one of the three pillars along with surgical procedures and 374 00:20:34,160 --> 00:20:37,400 radiology that support a lot of hospitals. So it could be destabilizing there. 375 00:20:37,740 --> 00:20:39,400 So on the one side we see this promise, 376 00:20:39,580 --> 00:20:43,960 but then you see the risk of particularly reimbursement being dropped because 377 00:20:43,960 --> 00:20:47,620 again, we're not thinking about the value of the labs, but rather just the cost. 378 00:20:47,620 --> 00:20:50,100 And the cost is such a small fraction of overall healthcare. 379 00:20:50,360 --> 00:20:54,860 And then there's regulatory things as well. How do we continue to work with, uh, 380 00:20:54,880 --> 00:20:55,360 you know, 381 00:20:55,360 --> 00:20:59,140 to work with other stakeholders so they can feel like we're safely innovating. 382 00:20:59,400 --> 00:21:00,620 The labs need to be, they're, 383 00:21:00,620 --> 00:21:03,180 they're really at this intersection between the practice, 384 00:21:03,280 --> 00:21:05,380 the medicine and science and technology. 385 00:21:05,440 --> 00:21:09,540 So we need to really be thoughtful about regulatory practices that might govern 386 00:21:09,540 --> 00:21:10,373 that. 387 00:21:11,350 --> 00:21:14,600 Zooming in on the policy side first, and then I'll share a thought with the, 388 00:21:14,600 --> 00:21:16,680 the medical side that you just described, Dr. Maurice, 389 00:21:16,740 --> 00:21:20,600 but you had mentioned the payers are being a bit more rigorous and challenging 390 00:21:20,620 --> 00:21:25,440 or prior offing the daylights out of those specialized expensive 391 00:21:25,530 --> 00:21:26,520 tests that can be ordered. 392 00:21:26,900 --> 00:21:30,360 And what you just described here is a drop in reimbursement for commonly ordered 393 00:21:30,410 --> 00:21:30,860 tests. 394 00:21:30,860 --> 00:21:35,440 So it seems like both the extraordinary and the ordinary are going through their 395 00:21:35,440 --> 00:21:38,080 own sets of reimbursement struggles. 396 00:21:39,310 --> 00:21:43,480 Yeah, they are. It's a bit of a silly crib, if you will. Um, they're the, uh, 397 00:21:43,610 --> 00:21:46,040 you'd at both ends. Um, but it does, 398 00:21:46,310 --> 00:21:50,640 it's just a real need to understand not just the role of 399 00:21:50,720 --> 00:21:52,600 laboratories in healthcare, 400 00:21:52,940 --> 00:21:57,400 but also to have a mind towards how that translates into the economics of 401 00:21:57,400 --> 00:22:00,240 healthcare and the sustainability of healthcare. So we can have more informed, 402 00:22:00,380 --> 00:22:04,080 either create for payers the tools that they need, that they, cause look, 403 00:22:04,100 --> 00:22:05,040 payers don't really, 404 00:22:05,470 --> 00:22:09,800 they use the private payers use things like prior auth because they just don't 405 00:22:09,800 --> 00:22:11,760 have very many uh, um, 406 00:22:11,890 --> 00:22:14,600 mechanisms or levers they can pull to control some of these things. 407 00:22:14,600 --> 00:22:19,160 So we have to understand that context and, and really focus on that. And, 408 00:22:19,180 --> 00:22:21,080 and same on on the, like I, 409 00:22:21,080 --> 00:22:24,320 like we talked about how do we start to create their payer databases. 410 00:22:24,320 --> 00:22:27,080 There's lots of places where you can go and create the financial models that 411 00:22:27,320 --> 00:22:29,080 demonstrate the economics of the, 412 00:22:29,080 --> 00:22:33,780 of the situation that will actually get to more to reimbursement policies 413 00:22:33,850 --> 00:22:38,100 that will actually drive healthcare behaviors in the direction that we wanna go. 414 00:22:38,360 --> 00:22:40,420 And a less frictionless way for patients. 415 00:22:40,420 --> 00:22:43,100 Cause it's really patients that get stuck in the middle. But that's, 416 00:22:43,100 --> 00:22:44,540 we have to really view it in that way. 417 00:22:44,560 --> 00:22:48,060 That's why I'm excited in my role now as the president and CEO of Mayo Clinic 418 00:22:48,060 --> 00:22:50,420 Labs, that's my focus now is thinking about that, 419 00:22:50,530 --> 00:22:54,900 that taking my 35 years of experience if we count medical school and trying to 420 00:22:54,900 --> 00:22:57,300 pivot that now to think about these issues. Mm-hmm. 421 00:22:57,340 --> 00:23:01,660 . And then the other part you mentioned about the digital pathology 422 00:23:03,210 --> 00:23:05,900 kind of last frontier in so many ways as you just described, 423 00:23:05,900 --> 00:23:06,980 for patients especially. 424 00:23:07,080 --> 00:23:10,580 But what struck me as you were talking about that where all that data lives 425 00:23:10,780 --> 00:23:15,460 together is how much more upstream opportunity there can be for, for patients, 426 00:23:15,680 --> 00:23:20,540 for care teams to have all that information stored in one place to be able to 427 00:23:20,540 --> 00:23:23,820 build upon it. It, it seems like so much of healthcare, 428 00:23:23,820 --> 00:23:27,580 there's so many problems downstream that seems like such a great and bright 429 00:23:27,580 --> 00:23:31,900 opportunity further upstream that could really be seized and a lot of value 430 00:23:32,220 --> 00:23:33,053 derived from. 431 00:23:33,860 --> 00:23:37,740 I I couldn't agree more. And I think that's, look, 432 00:23:37,860 --> 00:23:40,700 I I I love that I've been at Mayo for my career. Uh, 433 00:23:40,700 --> 00:23:44,180 my wife loves it cuz she's from Minnesota, so we've raised our family here. Uh, 434 00:23:44,280 --> 00:23:44,760 but uh, 435 00:23:44,760 --> 00:23:48,740 but the reality is that we need to think about ways that that knowledge and that 436 00:23:48,740 --> 00:23:52,220 places like Mayo and others, there's been many great healthcare institutions. 437 00:23:52,240 --> 00:23:54,820 How do we make that more scalable for patients, right? 438 00:23:55,130 --> 00:23:57,540 Mayo Clinic Laboratories and getting the testing out there was, 439 00:23:57,680 --> 00:23:58,740 was a first step in that. 440 00:23:59,160 --> 00:24:02,380 As we think more upstream and about how this data is coming together and created 441 00:24:03,120 --> 00:24:07,500 the digital technologies like Drer's vision around Mayo Clinic platform for 442 00:24:07,500 --> 00:24:10,300 Mayo. Those are the things that start to make that knowledgeable, scalable. 443 00:24:10,410 --> 00:24:12,620 Because if we're not thinking about access, 444 00:24:13,000 --> 00:24:15,020 if we're thinking about just building ivory towers, 445 00:24:15,330 --> 00:24:17,780 then we're not doing what we should be doing for healthcare. So, so I, 446 00:24:17,900 --> 00:24:21,180 I think that's the excitement for me is to think upstream cuz that's where that 447 00:24:21,380 --> 00:24:24,620 scalability of knowledge and knowledge exchange comes from. 448 00:24:26,300 --> 00:24:29,510 Well, Dr. Maurice, we've touched on so much in this interview, but you know, 449 00:24:29,510 --> 00:24:30,830 one thing we haven't talked about is, 450 00:24:30,850 --> 00:24:33,030 is your role and your professional journey. 451 00:24:33,250 --> 00:24:35,430 And like I had mentioned the introduction, you, 452 00:24:35,490 --> 00:24:37,670 you hold the number of roles at Mayo. 453 00:24:38,250 --> 00:24:42,150 I'm curious if you have any advice for colleagues listening who may like you 454 00:24:43,030 --> 00:24:46,950 transcend boundaries of specialist, researcher, executive, 455 00:24:47,700 --> 00:24:51,910 what is most important as you find yourself thriving in each of these related 456 00:24:52,090 --> 00:24:53,670 but distinct roles with Mayo Clinic? 457 00:24:55,650 --> 00:24:57,830 God, um, it's, uh, 458 00:24:57,830 --> 00:25:02,250 I think the one thing is that follow your curiosity. Continue to learn, 459 00:25:03,290 --> 00:25:06,370 continue to be open. I mean, everyone, I think my, 460 00:25:06,370 --> 00:25:10,290 where I am in my career is that I'm just been blessed to be around a lot of 461 00:25:10,290 --> 00:25:13,730 really smart people that have taught me lots of different things. And, and so, 462 00:25:13,730 --> 00:25:17,330 and then you just continue to accumulate different sorts of perspectives that 463 00:25:17,330 --> 00:25:21,090 become valuable to you and hopefully valuable to others as you go through your 464 00:25:21,090 --> 00:25:23,570 career. Um, so, and, and, uh, 465 00:25:23,570 --> 00:25:26,970 and the other thing is to really identify your passions and, and go with them. 466 00:25:27,150 --> 00:25:28,370 You know, it's, it's, uh, 467 00:25:28,480 --> 00:25:31,890 I've always been a very inquisitive person just because, you know, 468 00:25:31,950 --> 00:25:35,650 you were born when I was starting medical school doesn't need id to stop being 469 00:25:35,650 --> 00:25:38,970 inquisitive at this point, right? So I think those are, those are the things. 470 00:25:39,110 --> 00:25:43,490 But, um, surrounding yourself with good people, being curious, being humble, uh, 471 00:25:43,490 --> 00:25:45,570 hopefully I, I I embody some of those things. 472 00:25:45,690 --> 00:25:47,290 I think those are the real keys to me. 473 00:25:47,840 --> 00:25:48,673 Yeah. 474 00:25:49,030 --> 00:25:51,490 Is there anything we didn't touch on in our time together that you'd like to 475 00:25:51,490 --> 00:25:52,323 make mention of? 476 00:25:54,040 --> 00:25:58,620 God? Well, we talked about a lot, so, um, I don't know. I think we, 477 00:25:58,740 --> 00:26:01,700 I think we touched on the, on the, on the high points for sure. Great. 478 00:26:01,880 --> 00:26:04,740 Now we might get transcendent to the areas I shouldn't talk about on the 479 00:26:04,740 --> 00:26:05,050 podcast. 480 00:26:05,050 --> 00:26:09,100 Like the fact that I actually sing in public every year at Christmas for my, 481 00:26:09,100 --> 00:26:12,860 for the town halls, which stuff like that, which probably I shouldn't do, 482 00:26:12,960 --> 00:26:13,860 but . 483 00:26:14,250 --> 00:26:17,020 Well that's even all the more impressive given you are, you know, 484 00:26:17,020 --> 00:26:20,980 a lifelong red Rochester. I, I don't know if you live there, Dr. Maurice, 485 00:26:21,040 --> 00:26:24,660 but she nonetheless worked there for 35 years and sing every year. Um, 486 00:26:24,660 --> 00:26:28,620 you can't be that bad. So, , um, I, I wanna thank you for your time. 487 00:26:28,700 --> 00:26:29,940 I learned a lot from you today. 488 00:26:30,200 --> 00:26:34,180 Thanks for sharing your thoughts with our listeners and helping us see and 489 00:26:34,380 --> 00:26:36,500 remember the value of labs specifically. I, 490 00:26:36,500 --> 00:26:39,060 I wanna wish you continued to lock in your, in your role with Mayo. 491 00:26:39,690 --> 00:26:42,660 Well, thank you very much and again, really a pleasure. Uh, 492 00:26:42,660 --> 00:26:44,780 thanks for having me on and I, I've really enjoyed it.